A Review on Explainability in Multimodal Deep Neural Nets

17 May 2021

Papers citing "A Review on Explainability in Multimodal Deep Neural Nets"

19 / 19 papers shown

Title
Towards Vision-Language Mechanistic Interpretability: A Causal Tracing Tool for BLIP Vedant Palit Rohan Pandey Aryaman Arora Paul Pu Liang 16 20 0 27 Aug 2023
Causal Intersectionality and Dual Form of Gradient Descent for Multimodal Analysis: a Case Study on Hateful Memes Yosuke Miyanishi M. Nguyen 24 2 0 19 Aug 2023
Patchwork Learning: A Paradigm Towards Integrative Analysis across Diverse Biomedical Data Sources Suraj Rajendran Weishen Pan M. Sabuncu Yong Chen Jiayu Zhou Fei Wang 49 14 0 10 May 2023
Interpretable multimodal sentiment analysis based on textual modality descriptions by using large-scale language models Sixia Li S. Okada 25 3 0 07 May 2023
On the Robustness of Explanations of Deep Neural Network Models: A Survey Amlan Jyoti Karthik Balaji Ganesh Manoj Gayala Nandita Lakshmi Tunuguntla Sandesh Kamath V. Balasubramanian XAI FAtt AAML 19 4 0 09 Nov 2022
Is Multi-Modal Necessarily Better? Robustness Evaluation of Multi-modal Fake News Detection Jinyin Chen Chengyu Jia Haibin Zheng Ruoxi Chen Chenbo Fu AAML 22 9 0 17 Jun 2022
Explainable Misinformation Detection Across Multiple Social Media Platforms Gargi Joshi Ananya Srivastava Bhargav D. Yagnik Md Musleh Uddin Hasan Zainuddin Saiyed Lubna A Gabralla Ajith Abraham Rahee Walambe K. Kotecha 21 17 0 20 Mar 2022
Explainable AI (XAI): A Systematic Meta-Survey of Current Challenges and Future Opportunities Waddah Saeed C. Omlin XAI 34 409 0 11 Nov 2021
HEROHE Challenge: assessing HER2 status in breast cancer without immunohistochemistry or in situ hybridization Eduardo Conde-Sousa João Vale Ming Feng Kele Xu Yin Wang ... Guilherme Aresta Teresa Araújo Paulo Aguiar C. Eloy A. Polónia 20 28 0 08 Nov 2021
Zero-Shot Text-to-Image Generation Aditya A. Ramesh Mikhail Pavlov Gabriel Goh Scott Gray Chelsea Voss Alec Radford Mark Chen Ilya Sutskever VLM 253 4,735 0 24 Feb 2021
Unbox the Black-box for the Medical Explainable AI via Multi-modal and Multi-centre Data Fusion: A Mini-Review, Two Showcases and Beyond Guang Yang Qinghao Ye Jun Xia 87 478 0 03 Feb 2021
Beyond VQA: Generating Multi-word Answer and Rationale to Visual Questions Radhika Dua Sai Srinivas Kancheti V. Balasubramanian LRM 30 22 0 24 Oct 2020
Removing Bias in Multi-modal Classifiers: Regularization by Maximizing Functional Entropies Itai Gat Idan Schwartz A. Schwing Tamir Hazan 51 88 0 21 Oct 2020
Multimodal Research in Vision and Language: A Review of Current and Emerging Trends Shagun Uppal Sarthak Bhagat Devamanyu Hazarika Navonil Majumdar Soujanya Poria Roger Zimmermann Amir Zadeh 18 6 0 19 Oct 2020
Semantics of the Black-Box: Can knowledge graphs help make deep learning systems more interpretable and explainable? Manas Gaur Keyur Faldu A. Sheth 29 110 0 16 Oct 2020
Deep-HOSeq: Deep Higher Order Sequence Fusion for Multimodal Sentiment Analysis Sunny Verma Jiwei Wang Zhefeng Ge Rujia Shen Fan Jin Yang Wang Fang Chen Wei Liu 14 20 0 16 Oct 2020
Methods for Interpreting and Understanding Deep Neural Networks G. Montavon Wojciech Samek K. Müller FaML 234 2,231 0 24 Jun 2017
Towards A Rigorous Science of Interpretable Machine Learning Finale Doshi-Velez Been Kim XAI FaML 225 3,658 0 28 Feb 2017
Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding Akira Fukui Dong Huk Park Daylen Yang Anna Rohrbach Trevor Darrell Marcus Rohrbach 144 1,458 0 06 Jun 2016